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    • 专利摘要:
    The invention relates to a method for determining the structure of an electricity distribution network (10), comprising a power supply station (14) comprising one or more electrical power supply outlets (181, 182) of several electrical consumers (161, 162, 163), the method comprises the following steps: -a) acquiring first data relating to the electrical energy consumed by each consumer (161, 162, 163) during different time intervals, b) the acquisition of second data relating to the electrical energy delivered by each feeder (181, 182) during the different time intervals, - c) the generation of several different data sets, -d) the calculation of a first selection criterion for each data set, -e) selection of a first set of data sets from the generated sets, -f) determination of connection parameters.
    公开号:FR3035496A1
    申请号:FR1553646
    申请日:2015-04-23
    公开日:2016-10-28
    发明作者:Victor Gouin；Marie-Cecile Alvarez-Herault；Philippe Deschamps；Sylvain Marie；Yacine Lamoudi
    申请人:Schneider Electric Industries SAS；
    IPC主号:
    专利说明:

    [0001] The present invention relates to a method implemented by computer, for determining the structure of an electricity distribution network. , an associated computer program and a system for determining the structure of the electricity distribution network. In the field of electricity distribution, it is known to ensure the distribution of electricity to a plurality of electrical consumers via an electricity distribution network comprising an electrical transformer station, the substation having electrical outlets of power supply of electrical consumers. The transformer station is, for example, a high-voltage / medium-voltage transformer station (HTB / HTA) or medium-voltage / low-voltage transformer (HTA / LV), and the electrical feeders are medium or low voltage feeders.
    [0002] The high voltage corresponds to a voltage higher than 50 kVolts (kV), the medium voltage corresponds to a voltage of between 1 kV and 50 kV and the low voltage corresponds to a voltage of less than 1 kV. In such power distribution networks, the consumers are powered either three-phase or single-phase, and the transformer station is configured to distribute the electrical power it receives between different electrical outputs. However, the structure, and more specifically the mapping, of electricity distribution networks supplying electric consumers is generally poorly known. However, knowledge of the structure of such networks has become essential to meet the constraints that national regulators impose on electricity distributors, particularly in terms of the quality of electricity supply. In fact, national regulators impose quality of service objectives on electricity distributors, and these must be measurable. Electricity distributors therefore need to know more about the structure of electricity distribution networks, in particular to locate any faults or failures on the network or to identify the most significant losses from the transformer station in terms of losses. electric. It is thus known from EP 2 458 340 A2 a method for determining the structure of a power distribution network from specific calculation means and information relating to the electrical energy consumed by each electrical consumer connected to the network and relating to the electrical energy delivered by each departure from the transformer station.
    [0003] However, the speed of execution, the accuracy and the reliability of such a method remain to be improved. The object of the invention is therefore to propose a method of robust determination of the structure of an electricity distribution network making it possible to determine the structure of the electricity distribution network in a safer, more reliable and faster way. . Such a method makes it possible to overcome any errors, for example related to inaccuracies in measuring the energy consumed and / or delivered or the absence of certain energy measurements. For this purpose, the subject of the invention is a method for determining the structure of an electricity distribution network, the method being implemented by computer, the distribution network comprising a feed station comprising one or more power supply feeders of several electrical consumers and comprising the following steps: -a) acquiring, for each electrical consumer, first data 15 relating to the electrical energy consumed by the electrical consumer during different time intervals, measured via a first energy measurement sensor, -b) acquiring, for each departure, second data relating to the electrical energy delivered by the departure during the different time intervals, measured via a second energy measurement sensor , 20 - c) the generation, via a generation module, of several different data sets, associated each one at one of the time intervals, each data set comprising the first and second data associated with said time interval, characterized in that the method further comprises the following steps: -d) calculating a first selection criterion for each set of data, the first selection criterion being a criterion chosen from a global rate of electrical energy losses between the starter (s) and the consumers and a difference in consumption of electrical energy between the various consumers, (e) selecting, by a selection unit and according to the first calculated selection criteria, a first set of data sets from the generated sets, -f) determining, from the first selected set, connection parameters , said parameters comprising for each electrical consumer an identifier of the feeder to which it is connected. Thanks to the invention, the steps of Electing the first set of data sets according to the first calculated selection criteria and determining the connection parameters from the first selected set makes it possible to more reliably and quickly determine the structure of the distribution network. electricity. According to other advantageous aspects of the invention, the determination method further comprises one or more of the following characteristics, taken alone or in any technically permissible combination: in the calculation step d), a second criterion for each generated data set is calculated, the second criterion being the other criterion chosen from a global rate of electrical energy losses between the starter (s) and the consumers and a difference in the consumption of electrical energy between the various consumers, 10 and, in the selection step e), the first set is selected according to the first and second calculated criteria; following the selection step e), the method comprises the following steps: -el) the calculation of a second selection criterion for each data set of the first set, the second criterion being the other criterion chosen from a global rate of electrical energy losses between the departure (s) and the consumers and a difference in consumption of electrical energy between the different consumers, -e2) the selection according to the second calculated selection criteria of a second set of data sets from the first set, the determination of the connection parameters then being carried out in the determination step f) as a function of the second set selected from the first set; during the determination step f), the connection parameters are determined separately for each start and independently of the second data relating to the electrical energy acquired for the other starts; during the determination step f), an equation system to be solved is determined from an electrical energy conservation postulate for each start according to which the energy delivered by the departure is substantially equal to the sum of the energy consumed by the initially connected electrical consumers and electrical losses; in the determination step f), the equation system is defined from the following equation: EDJk) .E (tk) + -2, k), 3035496 4 where n is the number of electrical consumers , j is a starting index varying from 1 to m, where m is the number of starts, i is an electrical consumer index varying from 1 to n, k is a data set index of the first set varying from 1 to w, where w is the number of data sets of the first set, tk is the time interval associated with the index data set k, is the connection parameter indicating whether the index consumer i is connected to the index start j , Eak) is the electrical energy consumed by the electrical consumer of index i 10 during the time interval tk, E Di (tk) is the electrical energy delivered by the departure of index j during the time interval tk, and ai and a 2, k are adjustment variables representative of electrical losses; the equation system is written in a matrix form as follows: A * z = B, where z = a11 B = EDI (ti and A = U 0 - - 0 with an1 EDI ED2 o - - - 0 U alm ED2 (tw) EDm (ti) 0 anm EDm (tk) aln aim, '2ii _a 2, E1 (t1) - - - E (t1) E1 (t) - - - Ecn (tw) - when the determination step, an optimization algorithm is used to solve the equation system, the optimization algorithm verifying: {Az = B 20 min fT .Z such that, where fT .z = [0 - - 0 1 --- 1 1 --- 11x z, lz zuz, i * 'w *. W *. U = and A including m * n columns and m * w lines; 3035496 5, with e between 0 and 0.5; 0 +00 - each start includes one or more phase electrical conductors, and, during acquisition step b), the second data is acquired for each phase electrical conductor and is energy related. electrical supply delivered by each phase electrical conductor, and, during the determination step f), the determined connection parameters comprise for each electrical consumer an identifier of the phase electrical conductor (s) to which it is connected; in the determination step f), the method comprises the following steps: 41) the pseudo-random selection of a third set of data sets included in the first set, -f2) the determination of the connection parameters from the third set selected from the first set; following selection step f1) and previously at the determination step f2), the method comprises the following steps: f3) the calculation of a repetition parameter, f4) the determination, from the third selected set of intermediate connection indices comprising for each electrical consumer an identifier of the feeder to which it is connected, -f5) the storage of the intermediate coupling indices, and -f6) the comparison of the repetition parameter with at least one predetermined repeat criterion, and, according to the result of the comparison step f6), performing a step of, on the one hand, the repetition of the selection steps f1), calculation f3), determination f4) , storing f5) and comparing f6) and, on the other hand, the step of determining f2) the connection parameters as a function of the stored intermediate interchange indices; the method comprises the following step: f7) calculating, for each consumer and for each start, an assignment number relative to the number of times that the intermediate connection indices stored in memory indicate that the consumer is initially connected and, in the determination step f2), the connection parameters are determined from the calculated assignment numbers. The invention also relates to a computer program comprising software instructions, which when executed by a computer implement the method defined above. Another subject of the invention is a system for determining the structure of an electricity distribution network, the distribution network comprising a supply station comprising one or more electrical power supply outlets of several units. electrical consumers, the system comprising: - for each electrical consumer, a first sensor for measuring first data relating to the electrical energy consumed by the consumer during different time intervals, - for each start, a second sensor for measuring second data relating to the electrical energy delivered by the start during the different time slots, - a module for acquiring the first and second data, - a module for generating several different data sets, each associated with one of the time intervals , each data set comprising the first and second data associated with audio it is a time interval, characterized in that the determination system further comprises: a calculation module of a first selection criterion for each data set, the first selection criterion being a criterion chosen from an overall loss rate of electricity between the starter (s) and the consumers and a difference in consumption of electrical energy between the different consumers, 25 - a selection module, according to the first calculated selection criteria, of a first set of games of data from the generated sets, and - a determination module, from the first selected set of connection parameters, said parameters comprising for each electrical consumer an identifier of the start to which it is connected.
    [0004] The invention will be better understood and other advantages thereof will appear more clearly in the light of the description which follows, given solely by way of nonlimiting example, and with reference to the drawings in which: Figure 1 is a diagrammatic representation of an electricity distribution network comprising a feed station having a plurality of feeders for supplying electrical energy to a plurality of electrical consumers; FIG. 2 is a flowchart of a method for determining the structure of the electricity distribution network of FIG. 1, according to a first embodiment of the invention; FIG. 3 is a flowchart similar to that of FIG. 2, according to a second embodiment of the invention; FIG. 4 is a flowchart similar to that of FIG. 2, according to a third embodiment of the invention; and FIG. 5 is a flowchart similar to that of FIG. 2, according to a fourth embodiment of the invention.
    [0005] In FIG. 1, an electricity distribution network 10 is associated with a system 12 for determining the structure of the electricity distribution network 10. The distribution network 10 comprises a supply station 14 for electrical energy from several electrical consumers 16 ,. The feed station 14 comprises electrical feeds 18, electrical power supply of the electrical consumers 16 ,, 15 with i an electrical consumer index and a starting index. The electrical consumer index i varies from 1 to n, where n is the number of electrical consumers 16, and the starting index j varies from 1 to m, where m is the number of electrical outputs 18,. In the example of FIG. 1, the number n of electrical consumers 16, is equal to 3, and the number m of electrical outputs 18, is equal to 2.
    [0006] The determination system 12 comprises, for each electrical consumer 16, a first energy measurement sensor 20 and a transmission module 21 of the energy measurements made by the corresponding first sensor 20. The determination system 12 comprises, for each start 18 ,, a second sensor 22, for measuring energy.
    [0007] The determination system 12 also comprises an information processing unit 24 formed for example of a processor 26 and a memory 28 associated with the processor 26. The supply station 14 is, for example, a transformer station medium voltage / low voltage connected between a medium voltage network, not shown, and a low voltage network 30 corresponding to the electrical consumers 16,. The feed station 14 includes, at each start 18, the corresponding second sensor 22. The electrical consumers 16, are connected to the power station 14 via the departures 18,. More specifically, in the example of FIG. 1, the electrical consumers 161, 162 are connected at the start 181 and the electrical consumer 163 is connected to the start 182.
    [0008] The electrical consumers 16, are either three-phase and supplied by the start 18, corresponding via four electrical conductors 32 ,, 34 ,, 36 ,, 38 ,, that is to say three phase electrical conductors 32, 34 , 36, and an electrical conductor of neutral 38 ,, either single-phase and supplied by the start 18, corresponding via two electrical conductors 5: that is to say, for example a phase conductor 32,, 34, or 36 , and the neutral conductor 38, In the example of Figure 1, the electrical consumer 161 is three-phase and the electrical consumers 162, 163 are single-phase. Each electrical consumer 16 includes one of the first sensors 20, 10 corresponding and one of the corresponding transmission modules 21. Each electrical consumer 16 is, for example, a communicating power consumption counter, able to measure first data Ec, relating to the electrical energy consumed by the electrical consumer 16 ,, via the corresponding first sensor 20, and to be transmitted the first data Ec, to the processing unit 24 via the corresponding transmission module 21. Each feeder 18 is a three-phase feeder and comprises the three corresponding phase conductors 32, 34, 36 and the corresponding neutral conductor 38. In a variant, not shown, the electrical outputs are single-phase and comprise a phase conductor and a neutral conductor. According to yet another variant, not shown, some departures are single-phase and others are three-phase. Each first sensor 20 is capable of measuring the first data E (t1) relating to the electrical energy consumed by the corresponding electrical consumer 16, during different time intervals t1. More generally, the first sensors 20, are configured to measure the first 25 data E (t1) during the same time intervals tl, the first data Ec, (ti) measured at each electrical consumer 16, being measured synchronously. Each transmission module 21 is able to transmit the first data Ec, (ti) measured by the first sensor 20, corresponding to the destination of the processing unit 24. Advantageously, each transmission module 21 is able to transmit with the first data Ec, (ti) a first piece of information relating to the time interval during which the first data has been measured. Each second sensor 22 is capable of measuring second data EDA) 35 relating to the electrical energy delivered by the start 18, corresponding during the different time intervals t1.
    [0009] The first E (t1) and second ED, (0 measured data are then synchronized in the sense that they are measured during identical time intervals ti Each second sensor 22, is also configured to transmit, via a respective electrical link 40 , the second ED data, (0qu'il it measures the processing unit 24. Advantageously, each second sensor 22, is configured to transmit with the second ED data, (ti) a second information relating to the time interval t during which the second data ED, (ti) were measured.
    [0010] The first Ec (t1) and second ED, (ti) data are, for example, active energy measurements. More precisely, in the remainder of the description, it is considered that the first Ec (t1) and second ED (ti) data are active energy measurements. Alternatively, the first Ec, (t) and second ED, (ti) data are reactive energy measurements, apparent energy measurements, active power measurements, reactive power measurements, power measurements. apparent or intensity measurements. The processor 26 is configured to execute software included in the memory 28.
    [0011] The memory 28 comprises a software 41 for acquiring the first E (t1) and second ED, (0 data, a software 42 for generating several different data sets I, from the first data E (t1) and second data. ED data, (0 acquired in the same time interval t, and software 44 for calculating a first selection criterion C11 for each data set Jel.
    [0012] The memory 28 also includes a software 46 for selecting a first set of data sets Jel, as a function of the first selection criteria C11 calculated by the calculation software 44 and a software 48 for determining connection parameters to the data set. , said connection parameters comprising for each electrical consumer 16, an identifier of the start 18, to which it is connected.
    [0013] The acquisition 41, generation 42, calculation 44, selection 46 and determination 48 software correspond to software instructions and form a computer program capable of being executed by a computer. The computer corresponds, for example, to the processing unit 24. The acquisition software 41 is clean, for example, to transmit to each electrical consumer 16, and in particular to each first sensor 20, an order of 3035496. measuring the first data E (t1) and a transmission order of the first data E (0, in order to recover the first data, and the acquisition software 41 is, for example, configured to transmit to each start 18, and in particular to each second sensor 22, a measurement command 5 of the second data ED, (0 and a transmission command of the second data ED, (0, in order to recover the second data ED, (0. Advantageously the measurement orders of the first E (t1) and second ED, (0 data are transmitted simultaneously to all departures 18, and all consumers 16,.
    [0014] The generation software 42 is configured to generate the data sets Je, which are each associated with one of the time intervals t, and which comprise the first Ec, (11) and second ED, (ti) data associated with said interval. In other words, the generation software 42 selects the first Ec, (11) and second EDA) data measured during the different time intervals 11, to create the data sets Jel. The calculation software 44 is adapted to calculate, for each data set Jel, the first selection criterion C1, which is chosen from a global rate of electrical energy losses between the feeders 18, and the electrical consumers 16, and a difference in power consumption between the different consumers 16 ,. The losses of electrical energy include both the so-called technical losses, for example related to losses Joule during the flow of current between the departures 18j and the consumers 16i, the so-called non-technical losses, which are for example related to the theft of electricity, the fact that consumers are connected to the distribution network 10 without the information processing unit 24 is informed and defective first 20, 25 sensors. If the first selection criterion C1 is, for example, the overall rate of electrical energy losses between the feeders 18, and the consumers 16 ,, the first selection criterion C1 is calculated from the following formula: Cl = 7AE (t1) = EDJ (ti) i = 1 (1) J = 1 where I is a dataset index and ranges from 1 to r, where r is the number of data sets generated by the generation software 42, t, is the time interval associated with the data set of index I, E (t1) is the electrical energy consumed by the electrical consumer of index i during the time interval t, and ED (t) is the electrical energy delivered by the departure of index j during the time interval If the first selection criterion C1 is, for example, the difference in electrical energy consumption between the different consumers 16, the first criterion of selection Ci is calculated from the following formula: Cli = Var (Eci (tk), - - -, En, (tk)), (2) where Var is the variance function. Alternatively, if the first selection criterion C1 is, for example, the relative deviation of electrical energy consumption between the different consumers, the first selection criterion C1 is calculated from the following formula: = Var ( Eci (tk), - - -, E (tk)) Cl, (3) Moy (Eci (tk), - - -, E (tk)) 'where Moy is a mean function, such as an arithmetic mean, The selection software 46 is configured to select the first set En, 15 of data sets from the data sets I, generated by the generation software 42, according to the first selection criteria C1, calculated . The selection software 46 is, for example, configured to compare the first criteria C1 with a first predetermined variable V1 and to select the data sets Je, for which the first criterion Ci is smaller than the first predetermined variable Vl.
    [0015] The determination software 48 is configured to determine the connection parameters to from the first set En, selected. The determination software 48 is, for example, configured to establish or determine an equation system to be solved from an electrical energy conservation postulate for each start 18J, wherein the energy delivered by the departure 25 18, is substantially equal to the sum of the energy consumed by the electrical consumers 16, connected to the start 18, and electrical losses. The equation system is, for example, defined from the following equation: EDi (tk) = I (aii.E (tk) + a1 .'-a2; k) (4) i = 1 where n is the number of electrical consumers, j is a starting index varying from 1 to 30 m, where m is the number of starts, i is an electrical consumer index varying from 1 to n, 3035496 12 k is a Jek dataset index of the first set En, varying from 1 to w, where w is the number of data sets Jek of the first set Eni, tk is the time interval associated with the data set Jek of index k, is the connection parameter indicating whether the consumer of index i is connected at the beginning of index j, Eak) is the electrical energy consumed by the electrical consumer of index i during the time interval tk, EDJ (tk) is the electrical energy delivered by the starting of index j during the time interval tk, and 10 1jk and a2, k are adjustment variables representative of the electrical losses, ie e of the gap for each Jek data set and for each start 18, between the electrical energy delivered by the departure 18, and the electrical energy consumed by the electrical consumers 16, connected to the departure of index j. The equation system is then written, for example, in a matrix form in the following manner: A * z = B, (5) E (t E (tw) E D2 (t and A = [D / w, ' , / wm representing the matrix E D2 (tw) EDm (ti) E Dm ('k) a11 an1 alm where z = anm J111, B = J 211 J _ mw_ U 0 o E1 (t1) --- E (t1 ) _E1 (t) --- E (t) _ unit of size w * m, with D = - -. 0, U = and D 0 --- 0 U including m * n columns and m * w lines. The determination software 48 is then configured to solve the equation system from an optimization algorithm verifying: az = B min f .Z such that / zz uz where fT .z = [0 - - 0 1 --- 1 1 --- 1] xz, f T corresponding to a cost function of m * nw * mw * m -e the optimization algorithm and z to an objective vector defined above and where , lz = 0 being of dimension m * n + 2 * w * m and including m * n times the value -e and 2 * w * m times the 13 (6) -e 0, lz 5 value 0 and uz = 1 + e, uz being of dimension m * n + 2 * w * m and including m * n times the 1 + e +00 +00 value (1 + e) and 2 * w * m times the value +.0, with ecompris between 0 and 0.5, preferably between 0 and 0.1, more preferably equal to 0.05. The optimization algorithm is able to determine the objective vector z and thus the connection parameters for which the function fT.z is minimized. Specifically, the determination software 48 is configured to start from a randomly selected initial solution vector X = and to iteratively converge to a solution. At each iteration, the adjustment variables i, k, a2, k and the function fT.z are calculated and make it possible to decide on the next solution vector X.
    [0016] More specifically, at each iteration, the optimization algorithm balances the energy differences with the adjustment variables a1, k, a2 jk so that the equalities of the equation system are verified. Thus, if the energy delivered on a departure of index j is surplus, the corresponding adjustment variable alik is increased and if this energy is deficient, the corresponding variable a2 jk is increased. Thus, the more the connection parameters to respect the principle of conservation of energy, the more the adjustment variables are weak. The objective is to minimize the adjustment variables, which results in the objective function f T .zjk + a2) j = 1 k = 1 The matrices /, and u, limit the connection parameters to the input and output. 1 + e and the adjustment variables al jk and a2jk between 0 and + CC). More precisely, when the optimization algorithm is applied, the connection parameters at are real numbers, which makes it possible to relax the constraints. Then, following the application of the optimization algorithm, the determination software 48 is configured to set the values of the connection parameters to 0 or 1 according to their value following the application of the optimization algorithm. The value 0 indicates a non-connection of the consumer of index i at the beginning of index j, whereas the value 1 indicates a connection of the consumer of index i at the beginning of index j. The determination software 48 is, for example, configured to determine the values of the connection parameters following the application of the optimization algorithm 20 by the following equation: 1 if ati = max (ai) ati = 0 otherwise Thus, according to equation (7) above, each consumer 16 is connected to a single feeder 18. Furthermore, the processing unit 24 is configured to identify, as a function of the determined connection parameters. and from, for example, an identification software, not shown, included in the memory 28, subsets of consumers, with each subset of consumers that corresponds to the set of consumers 16, connected to the same departure 18 ,,. (7) In a variant, the determination software 48 is configured to determine the connection parameters separately for each start and independently of the second electrical energy data acquired for the other starts.
    [0017] According to this variant, an optimal equation system is determined for each departure and the optimization algorithm is applied to each optimal equation system. This results in m optimal equation systems solved independently via the optimization algorithm. Thus, for the departure of index 1, the corresponding system of optimal equation satisfies: ## EQU1 ## where z1 = B1 = and Al [U with a2iw_E D1 ( E1 (t1) --- E (t1) U = _E1 (t) --- E (t) _ Then, according to this variant, the determination software 48 is, for example, able to determine the values of the connection parameters via equation (7).
    [0018] According to another variant, the determination software 48 is configured to determine the connection parameters for each phase electrical conductor 32, 34, 36, and not simply for each start 18,. According to this other variant, the equation system then comprises as much equation as phase electrical conductors 32, 34, 36, and the variables described above and relating to a specific departure are then relative to a specific phase conductor. Thus, the second sensors 22, measure the electrical energy delivered by each phase conductor 32 ,, 34 ,, 36, and not each departure 18 ,, the connection parameters are determined for each phase conductor 32, 34, , 36, and the adjustment variables are determined for each phase conductor 32, 34, 36,. According to this other variant, for example, each electrical conductor is identified by an index and the variable j, presented in the above equations, then corresponds to an electrical phase conductor index and 3035496 16 ranging from 1 to u, with u the number of electrical phase conductors which is equal to 3 * m, ie 6 in the example of FIG. 1. Several embodiments of a method for determining the structure of the electrical distribution network 10, implemented via the processing unit 24, and more generally via the determination system 12, will now be presented. According to a first embodiment described hereinafter with reference to FIG. 2, the method comprises an initial step 100 for acquiring main data of the distribution network 10. The main data comprise, for example, the total number n of consumers 16 ,, the total number m of feeders 18J, the first measured data E (t measured, the second measured data ED, (ti) and the different time intervals t, associated with the first and second measured data. initial step 100, the acquisition software 41 controls, for example, the measurement, by each first 20 and second 22, sensors, first E (t1) and second Er)] (t1) data during time intervals t, and the transmission of the first 15 Ec (t1) and second EDJ (t1) data which are then associated with the time interval t, during which they were measured, via, for example, the first and second information. Then, during a generation step 102, the generation software 42 generates several different sets of data Je, each associated with one of the time intervals 20 t, and which comprise the first E (t1) and second ED, (ti) data associated with said time interval Then, during a calculation step 104, the calculation software 44 calculates the first selection criterion C1, for each data set Jel. The first selection criterion C1 is, for example, the overall rate of electrical energy losses between the feeders 18, and the consumers 16,. Then, during a selection step 106, the selection software 46 selects the first set En, based on the first selection criteria C1, calculated. The first set En is selected from the data sets generated in step 102. In the selection step 106, the selection software 46 compares, for example, the first criteria C1 with the first predetermined variable V1, the value of the first predetermined variable V1 being for example defined during the acquisition step 100. The selection software 46 then selects the data sets Je, for which the first criterion Ci is less than the first predetermined variable VI.
    [0019] Finally, during a determination step 108, the connection parameters are determined via the determination software 48 and from the first set En, selected. More specifically, the determination software 48 determines the equation system 5 to be solved from, for example, equation (4), as discussed above. Then, as presented above in the description of the determination system 12 and equation (5), the optimization algorithm is applied to the equation system to determine the connection parameters to. Alternatively, in the determining step, the determination software 48 determines the optimal equation systems, as presented above via equation (8), and applies the optimization algorithm to each system of determination. optimal equation. The speed of determination of the connection parameters is then improved, since the optimal equation systems comprise a limited number of equations. In the first embodiment, making a selection of the Jek data sets eliminates the I data sets, for which the losses are greatest, since these data sets may lead to an erroneous determination of the data sets. connection parameters. Thus, according to the first embodiment, the connection parameters determined in the, are determined more surely with respect to the known methods of the state of the art and the reliability of the determination method is improved. In addition, the optimization algorithm used makes it possible to use an indifferent number of Jek data sets during the determination step 108, even if it is preferable that the number of data sets of the first set be greater than or equal to equal to the total number n of consumers 16 ,.
    [0020] According to a second embodiment of the invention described hereinafter with reference to FIG. 3, the method comprises steps 200, 202, 204, 206, 208 identical to steps 100, 102, 104, 106, 108 of FIG. first embodiment and, in step 204, a second selection criterion C2 is calculated for each set of data generated. The second selection criterion C2 is different from the first criterion C1, and is chosen from a global rate of electrical energy losses between the starter (s) and the consumers and a difference in consumption of electrical energy between the different consumers. Thus, in step 204, each first criterion C1 is, for example, the overall loss rate relative to the data set Je, corresponding and each second criterion C2, is the difference in electrical energy consumption relative to the data set I, corresponding, and is calculated via equation (2) or equation (3).
    [0021] Then, during the selection step 206, the selection software 46 selects the first set As, based on the first selection criteria C1, and the second selection criteria C2, calculated. The first set En, is selected from the data sets generated in step 202. During the selection step 206, the selection software 46 compares, for example, the first criteria C1, with the first variable V1 and the second criteria C2, with a second predetermined variable V2. The value of the second predetermined variable V2 is, for example, defined during the acquisition step 200. The selection software 46 then selects the data sets for which the first criterion C1 is less than the first predetermined variable V1 10 and the second criterion C2 is smaller than the second predetermined variable V2. Finally, during the determination step 208 the connection parameters are determined via the determination software 48 and from the first selected set Enl. The second embodiment makes it possible to refine the selection of the data sets with respect to the first embodiment and thus to select data sets from which the risk of error in the determination of the connection parameters is minimized. The accuracy, speed and reliability of the determination method are thus improved. According to a third embodiment of the invention described hereinafter with reference to FIG. 4, the method comprises steps 300, 302, 304, 306, 310 identical to steps 100, 102, 104, 106, 108 of FIG. first embodiment and, following step 306 and previously at step 310, the method comprises a step 307 of calculating a second selection criterion C2k for each set of data of the first set En ,, the second criterion C2k being different from the first criterion and being selected from a global rate of electrical energy losses between the one or more departures 18, and the consumers 16, and a difference in power consumption between the different consumers 16,. In the third embodiment, each first criterion C1 is, for example, the overall loss rate relative to the corresponding data set generated in step 302, and each second criterion C2k is the difference in power consumption. relative to the corresponding dataset of the first set Enl. Following the calculation step 307, during a selection step 308, a second set En2 of data sets is selected from the first set Enl. Then, the first set En, is, for example, set equal to the second selected set En2 to perform the determining step 310 according to the second set selected En2.
    [0022] The third embodiment makes it possible to refine the selection of the data sets with respect to the first embodiment, and thus to select data sets from which the risk of error in the determination of the connection parameters is minimized. The accuracy, speed and reliability of the determination method are thus improved. According to a fourth embodiment of the invention described hereinafter with reference to FIG. 5, the method comprises steps 400, 402, 404, 406 identical to steps 100, 102, 104, 106 of the first embodiment. Then, following the selection step 406, the method comprises a step 408 for determining the connection parameters. Specifically, in step 408, the method comprises a first substep 408A pseudo-random selection of a third set of data sets En3 included in the first set Eni. Then, during a calculation sub-step 408B, a repeat parameter R1 is calculated. The repetition parameter R1 corresponds to a number of iterations of the selection sub-step 408A. Then, during a sub-step of determination 4080, intermediate indices b ,, of connection, indicating for each consumer 16, the start 18, to which it is connected, are determined from the third selected set En3. More generally, the intermediate indices b ,, comprise for each electrical consumer 16, an identifier of the start 18j to which it is connected. The determination sub-step 4080 is analogous to the determination step 108 of the first embodiment, but is performed from the third set En3. Then, during a storage sub-step 408D, the intermediate connection indices b ,, are stored by the memory 28.
    [0023] Then, during a calculation sub-step 408E, performed for each consumer 16, and for each start 18 ,, an assignment number NA ,, relating to the number of times the stored intermediate connection indices indicate that the consumer 16, is connected to the start 18, is calculated. The assignment number NA ,, is, for example, calculated by the following formula: N (bu = 1) NAu =, where N (bij 1) corresponds to the number of times the intermediate indices n b, stored, are equal to 1 for the consumer 16, of index i and the departure 18, of index j and NT corresponds to a total number of iterations of the substep selection 408A. Advantageously, the total number of iterations NT is initialized earlier than the execution of the selection sub-step 408A and incremented by 1 each time the substep of selection is executed. It should be noted that the number of intermediate connection indices stored for a given electrical consumer 16 and a given start 18 is equal to the number of iterations of the selection sub-step 408. Advantageously, the assignment numbers calculated are stored after the calculation sub-step 408E. Then, during a comparison sub-step 408F, the repetition parameter R-1 is compared with a predetermined repeat criterion CR1. The predetermined repeat criterion CR1 is, for example, initialized during the acquisition step 400. The repeat criterion CR1 is, for example, a minimum number of iterations of the selection sub-step 408A. If during the comparison sub-step 408F, the repeat parameter is less than the repeat criterion, then the selection steps 408A, 408B calculation, 4080 determination, 408D storage, 408E calculation and 408F comparison are repeated. If during the comparison sub-step 408F, the repetition parameter R-1 is greater than the repeat criterion CR1, then a substep 408G for determining the connection parameters a ,, is performed.
    [0024] In the determination sub-step 408G, the connection parameters are determined from the selected third set or sets En3, and more precisely according to the intermediate connection indices b ,, stored in the storage sub-step 408D. , and even more precisely according to the assignment numbers NA ,, calculated at the last iteration of the sub-step 408E. More precisely, for each electrical consumer 16 ,, the starting index j corresponding to the assignment number NA, the largest is identified, and the connection parameter to the corresponding consumer 16, and said departure 18, is fixed equal to 1, the other connection parameters relative to said consumer being set equal to 0. Advantageously, if in the sub-step 408G determination all the assignment numbers relating to a consumer 16, are less than a first threshold predetermined If, for example equal to 0.6, then a connection identification error for said consumer 16, is identified. Alternatively, if the number of iterations of substep 408A is greater than 2, then, during computation sub-step 408E, and at each iteration of substep 408E, a first average of the numbers allocation NA, calculated at each iteration of the sub-step 408E, for each consumer 16, and for each departure 18 ,, is calculated.
    [0025] Then, a second average of the assignment numbers NA, calculated at the last iteration, for each consumer 16, and for each departure 18, is calculated. Then, in the sub-step 408E, a difference between the first average and the second average is calculated.
    [0026] The first and second averages are, for example, arithmetic, geometric or quadratic averages. According to this variant, during the comparison sub-step 408F, the absolute value of the last calculated difference is compared with a second threshold. predetermined S2, for example equal to 0.1. Then, if during the comparison sub-step 408F, the repetition parameter R-1 is greater than the repeat criterion CR1 and the absolute value of the last calculated difference is smaller than the second threshold S2, then the substep 408G is done. Otherwise, steps 408A, 408B, 4080, 408D, 408E and 408F are repeated. The fourth embodiment makes it possible, especially when the number of iterations of the sub-step 408A is greater than 2, to determine the connection parameters to from third sets En3 of different data sets. Thus, the accuracy and reliability of the determination method are improved. In addition, the fourth embodiment advantageously makes it possible to identify each consumer 16, for which the associated departure 18j is determined with a good confidence index and each consumer 16, for which the associated departure 18j is indeterminate or determined with a bad one. confidence index. Indeed, as presented above, if during the determination sub-step 408G all the allocation numbers relating to a consumer 16, are lower than the first predetermined threshold Si, for example equal to 0.6, then an error identification of the connection for said consumer 16, is identified and the start 18j to which the consumer 16 is connected is indeterminate. Similarly, if during the determination sub-step 408G an allocation number relating to a consumer 16, is greater than a third predetermined threshold S3, for example equal to 0.95, then the connection of the consumer 16, initially 18j corresponding is identified with a good confidence index.
    [0027] Advantageously, the fourth embodiment makes it possible to associate, at each connection parameter with the fixed value equal to 1 during the determination sub-step 408G, a confidence index representing the probability that the determined connection is correct. The confidence index is for example equal to the assignment number NA ,, corresponding.
    [0028] The embodiments and variants envisaged above are suitable for being combined with each other, according to any technically permissible combination, to give rise to other embodiments of the invention. Thus, the second embodiment is capable of being combined with the fourth embodiment and the third embodiment is also adapted to be combined with the fourth embodiment.
    权利要求:
    Claims (14)
    [0001]
    CLAIMS 1. A method for determining the structure of an electricity distribution network (10), the method being implemented by computer (24), the distribution network comprising a supply station (14) comprising one or several feeders (18J) for supplying electrical energy to a plurality of electrical consumers (16,) and comprising the steps of: -a) acquiring (100; 200; 300; 400), for each electrical consumer (16), first data (Ec, (t1)) relating to the electrical energy consumed by the electrical consumer (16,) during different time intervals (t1), measured via a first energy measurement sensor (20,), -b ) acquiring (100; 200; 300; 400), for each start (18J), second data (EDJ (t1)) relating to the electrical energy delivered by the start (18J) during the different time intervals (t1); ), measured via a second energy measuring sensor (20J), c) generating (102; 202; 302; 402), via a generation module (42), several data sets (OJ different, each associated with one of the time intervals, each data set (I ')); comprising the first (E (0) and second (ED, (0) data associated with said time interval (t1), characterized in that the method further comprises the following steps: -d) the calculation (104; 204; 304; 404) of a first selection criterion (C11) for each data set, the first selection criterion (Cl ') being a criterion selected from a global rate of electrical energy losses between the departure (s) (18J) and the consumers (16,) and a difference in electrical power consumption between the different consumers (16,), -e) the selection (106; 206; 306; 406) by a selection unit (46) and according to first computed selection criteria (C1), of a first set (Eni) of data sets (Jek) among the generated games (OJ, -f) the determination (108; 208; 310; 408), from the first set (En1) selected connection parameters (a), said parameters (a, J) comprising for each electrical consumer (16), an identifier of the start (18J) to which it is connected.
    [0002]
    2. Method according to claim 1, wherein, during the calculation step d) (204), a second selection criterion (C21) for each set of data (OJ generated is calculated, the second criterion (C21) being the other criterion chosen from an overall rate of electrical energy losses between the feeder (s) (18J) and the consumers (16,) and a difference in electrical energy consumption between the different consumers (16,) , and wherein, in the step of selecting e) (206), the first set (En1) is selected according to the first (C1 ') and second (021) calculated criteria. 5
    [0003]
    3. A method according to claim 1, wherein, following the selection step e), the method comprises the following steps: -el) the calculation (307) of a second selection criterion (021) for each game data set (Jek) of the first set (En1), the second criterion (021) being the other criterion 10 chosen from a global rate of electrical energy losses between the departure (s) (18J) and the consumers (16,) and a difference in power consumption between the different consumers (16,), -e2) the selection (308) according to the second selection criteria (021) calculated from a second set (En2) of data sets from the first set 15 (En1), the determination of the connection parameters (a, J) being then carried out during the determination step f) (310) as a function of the second set (En2) selected from the first set (En1) . 20
    [0004]
    4. Method according to one of the preceding claims, wherein, during the determination step f) (108; 208; 310; 408), the connection parameters (a, J) are determined separately for each departure ( 18J) and independently of the second data (ED, (0) relating to electrical energy acquired for the other departures (18J).
    [0005]
    5. Method according to one of the preceding claims, wherein, during the determination step f) (108; 208; 310; 408), an equation system to be solved is determined from a postulate of conserving the electrical energy for each start (18J) according to which the energy delivered by the start (18J) is substantially equal to the sum of the energy consumed by the electrical consumers (16,) connected to the start (18J) and electrical losses.
    [0006]
    6. The method according to claim 5, wherein, in the determination step f) (108; 208; 310; 408), the equation system is defined from the following equation: EDi (tk where n is the number of electrical consumers (16,), j is a starting index (18,) ranging from 1 to m, m being the number of starts (18,), i is an electrical consumer index varying from 1 to n, k is a dataset index (Jek) of the first set (Eni) varying from 1 to w, w 5 being the number of data sets (Jek) of the first set (En1), tk is the time interval associated with the data set (Jek) of index k, is the connection parameter indicating whether the consumer (16,) of index i is connected at the start (18J) of index j, Eak) is the electrical energy consumed by the electrical consumer (16,) of index i 10 during the time interval tk, E Di (tk) is the energy electric delivered by the depa rt (18,) of index j during the time interval tk, and ai and a2, k are adjustment variables representative of electrical losses. 15
    [0007]
    7. The method of claim 6, wherein the equation system is written in a matrix form as follows: A * z = B, where z = a11 B = Em (ti) and A = U o 0 - .. o with an1 EDI (tw ED2 (t1) 0 - - 0 U alm ED2 (tw) E Dm (ta nm Dm (tk) aimw a2ii a2 mw_ U = E1 (t1) --- E (t1) and A comprising m * n columns and m * w lines _E1 (t) --- E (t) _ 20
    [0008]
    8. A method according to claim 7, wherein, during the determining step, an optimization algorithm is used to solve the equation system, the optimization algorithm verifying: 3035496 26 {Az = B min f T .Z such that, wherefT.z = [0 --- 0 1 --- 1 1 --- 1] xz, / zz, i * 'w * mw * m, with e between 0 and 0.5 . 5
    [0009]
    9.- Method according to one of the preceding claims, wherein each start (18J) comprises one or more phase electrical conductors, and wherein, in the acquisition step b), the second data (EDA)) are acquired for each phase electrical conductor and relate to the electrical energy delivered by each phase electrical conductor, and, in the determination step f) (108; 208; 310; 408), the connection parameters (a, J) comprise for each electrical consumer (16,) an identifier of the phase electrical conductor (s) to which it is connected.
    [0010]
    10. The method according to one of the preceding claims, wherein, during the determination step f) (408), the method comprises the following steps: f1) pseudo-random selection (408A) of a third set (En3) of data sets included in the first set (Ehl), - f2) determining (408G) the connection parameters (a, J) from the third set (En3) selected from the first set (Eni) ) - 20
    [0011]
    11. The method of claim 10, wherein, following the selection step (40) and the determination step (408G), the method comprises the following steps: 408B) of a repetition parameter (R1), 25 -f4) determining (4080), from the third set (En3) selected, intermediate connection indices (b, J) comprising for each electrical consumer (16 ,) an identifier of the start (18J) to which it is connected, -f5) the storage (408D) of the intermediate connection indices (b), and -f6) the comparison (408F) of the repeat parameter with at least one criterion of Predetermined repetition (CR1), lz -e and uz -e 0 3035496 27 and, depending on the result of the comparing step f6) (408F), performing a step of, on the one hand, the repetition of selection steps f1), calculation f3), determination f4), storage f5) and comparison f6) and, for other t, the determination step f2) of the connection parameters (a, J) as a function of the intermediate connection indices (b, J) stored.
    [0012]
    12. The method of claim 11, wherein the method comprises the following step: f7) calculating (408E), for each consumer (16,) and for each departure (18J), a number of allocation (NA) relating to the number of times that the intermediate connection indices (b, J) stored indicate that the consumer (16,) is initially connected (18J), and in which, during the determination step f2 ) (408G), the connection parameters (a, J) are determined from the calculated assignment numbers (NA). 15
    [0013]
    13. Computer program comprising software instructions, which when executed by a computer implement the method according to any one of the preceding claims. 20
    [0014]
    14.- System (12) for determining the structure of an electricity distribution network (10), the distribution network (10) comprising a feed station comprising one or more feeder feeders (18J). electrical energy of several electrical consumers (16,), the system comprising: - for each electrical consumer (16,), a first sensor (20,) for measuring first data (E (0) relating to the electrical energy consumed by the consumer (16,) during different time intervals (0, - for each start (18J), a second second data measuring sensor (22J) (ED, (0) relating to the electrical energy delivered by the departure ( 18J) during the different time intervals (0, 30 - a module (41) for acquiring the first (Ec, (0) and second (ED, M) data, - a module (42) for generating several data sets (I ') different, each associated with one of the time intervals (0, each ue data sets (I ') comprising the first (Ec, (0) and second (Ec, (0) data associated with said time interval (0, characterized in that the determination system (12) further comprises: 3035496 A module (44) for calculating a first selection criterion (C11) for each set (I ') of data, the first selection criterion (Cl') being a criterion selected from an overall loss rate of electrical energy between the one or more departures (18,) and the consumers (16,) and a difference in electrical energy consumption between the different consumers (16,), - a module (46) of selection, depending on the first computed selection criteria (C1), a first set (Eni) of data sets (Jek) among the generated games, and - a module (48) determination, from the first set (Eni) selected, parameters connection (a), said parameters (au) having for each electrical consumer (16,) an identifier the start (18J) to which it is connected.
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    同族专利:
    公开号 | 公开日
    AU2016202536A1|2016-11-10|
    AU2016202536B2|2019-09-26|
    US20160315469A1|2016-10-27|
    ES2651481T3|2018-01-26|
    EP3086093A1|2016-10-26|
    FR3035496B1|2017-05-26|
    US10431979B2|2019-10-01|
    EP3086093B1|2017-09-20|
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    申请号 | 申请日 | 专利标题
    FR1553646A|FR3035496B1|2015-04-23|2015-04-23|METHOD AND SYSTEM FOR DETERMINING THE STRUCTURE OF AN ELECTRICITY DISTRIBUTION NETWORK AND ASSOCIATED COMPUTER PROGRAM|FR1553646A| FR3035496B1|2015-04-23|2015-04-23|METHOD AND SYSTEM FOR DETERMINING THE STRUCTURE OF AN ELECTRICITY DISTRIBUTION NETWORK AND ASSOCIATED COMPUTER PROGRAM|
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    AU2016202536A| AU2016202536B2|2015-04-23|2016-04-21|Method and system for determining the structure of an electricity transmission grid and associated computer program|
    EP16166742.3A| EP3086093B1|2015-04-23|2016-04-22|Method and system for determining the structure of an electricity distribution network and related computer program|
    ES16166742.3T| ES2651481T3|2015-04-23|2016-04-22|Procedure and system for determining the structure of an electricity distribution network and associated computer program|
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